Methods for studying the behaviour of on-off feedback systems, with the emphasis on steady-state periodic phenomena, are presented in this thesis. The two main problems analyzed are (1) the determination of the periods of self and forced oscillations in single-, double-, and multiloop systems containing an arbitrary number of on-off elements; and (2) the investigation of the asymptotic stability in the small of single-loop systems containing one on-off element which may or may not have a linear region of operation. To study the periodic phenomena in on-off systems, methods of determining the steady-state response of a single on-r-off element are first described. Concepts pertaining to the steady-state behaviour are then introduced: in this respect it has been found that generalizations of the concepts of the Hamel and Tsypkin loci and also of the phase characteristic of Neimark are useful in the study of self and forced oscillations. Both the Tsypkin loci and the phase characteristic concepts are used to determine the possible periods of self and forced oscillations in single- and double-loop systems containing an arbitrary number of on-off elements; these concepts are also applied to multiloop systems. On-off elements containing a linear region of operation, called a proportional band, are then described: both the transient and periodic response are presented. An approximate method for determining the periodic response is given. The concept of the Tsypkin loci is used to determine the possible periods of self and forced oscillations in a single-loop system containing one on-off element with a proportional band. The asymptotic stability in the small, or local stability, of the periodic states of single-loop systems containing one ideal on-off element has been considered by Tsypkin. In this thesis, Tsypkin's results have been generalized to include the cases of on-off elements containing a proportional band. The stability of such systems is determined by the stability of equivalent sampled-data systems with samplers having finite pulse widths. Finally, this stability problem is solved by a direct approach, one that makes use of the physical definition of local stability; the results obtained by this method agree with those derived by the sampled-data approach. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

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Call number: LD2668 .T4 1960 S75

Call number: LD2668 .T4 1962 W36

Call number: LD2668 .T4 1966 H489 / Master of Science

Call number: LD2668 .T4 1966 F771 / Master of Science

published_or_final_version / Mechanical Engineering / Doctoral / Doctor of Philosophy

M.Ing. / This research project is dedicated to the automation of environmental control within greenhouses. To create an optimal climate in the greenhouse, the main environmental parameters that need to be controlled are temperature, humidity and light intensity. As a result of process dead times and the extreme interdependence of these parameters, the control problem can be classified as non-linear and multi-variable. In the past, most greenhouse environmental control systems depended on the decision making of an experienced human operator. This often gave rise to trial and error, especially when new species were established. With the current advances in "intelligent" control systems and high accuracy sensors, more and more of the decisions involved in greenhouse control can be automated. In this way more emphasis can be placed on emulating the abilities of an expert operator, by means of a computerbased automatic control system. In this research project, "intelligent" as well as "non-intelligent" control techniques, for addressing the problem of automated climate control in a greenhouse, are investigated. These include PID-control as a "non-intelligent" technique, and rule-based fuzzy logic control and self-learning fuzzy logic control as two "intelligent" control techniques. These techniques are all applied to experimental greenhouse which is equipped with management mechanisms, such as fans, heaters, sprinklers and lights. The results of the experiments are evaluated according to two performance parameters: the Control Performance Index (CPI) and the Mean Square Error (MSE). The three techniques are not only assessed for their efficiency, but also for their applicability to the greenhouse environmental problem. Each of the control techniques has a unique characteristic response to the non-linear, non-stationary, multi-variable problem of environmental control and are subsequently addressed in the respective chapter.